Agricultural mechanization is an important symbol of agricultural modernization, and agricultural equipment is the carrier of agricultural modernization and thus an important tool used to promote agricultural mechanization [1
]. The implementation of China’s Agricultural Mechanization Promotion Law in 2004 and the subsidy policy for the purchase of agricultural machinery in 1998 have played especially significant roles in improving the agricultural equipment level (AEL) and the agricultural mechanization level (AML) [2
]. From 2000 to 2014, the level of the comprehensive mechanization of crop cultivating, sowing, and harvesting in China increased from 32.3% to 61.6%, with an average annual increase of 2.25%. The total power of agricultural machinery during this period increased from 525 million kilowatts to 1081 million kilowatts, with an average annual increase of 5.71%. China’s basic national conditions are that there are more people and less land available than ever before, with less than 0.1 ha of cultivated area per person, approximately 0.63 ha per rural laborer, and low farmer income levels [3
]. These conditions effectively prevent China from following the development path of using large-scale agricultural machinery, like that purchased by farmers in European and American countries. Correspondingly, China cannot follow the path of using small-scale agricultural machinery with higher value, like that purchased by Japanese and Korean farmers. With the development of agricultural mechanization, however, China has explored its own road to mechanization.
China’s agriculture has experienced a large expansion of machine investments by farmers and machine rental services provided by specialized agents, which has contributed to the mechanization of agricultural production [4
]. Previous literature on the agricultural mechanization in China has concluded that the agricultural mechanization has increased the grain yield and ensured food security in China [7
]. At present, the agricultural mechanization in China is in the transition period from whole process mechanization to comprehensive mechanization [10
]. The development of agricultural mechanization was consistent with China’s new-type urbanization [11
]. Because of the continuous advancement of China’s urbanization process and the massive transfer of rural labor, China’s agriculture is developing toward a reliance on more machinery input [12
]. The increase in non-agricultural wage rates has led to an expansion of self-cultivated land size, and scale economies are emerging in Chinese agriculture with mechanization [8
]. The main problems in the development of China’s agricultural mechanization are concentrated in the imbalance of regional and field development, and the incoordination of investment and service [4
]; therefore, knowing which factors motivate the AML is of great importance.
Some studies have conducted sufficient research on the factors influencing China’s AML [5
]. These studies have found that the scale of farmland management, agricultural labor transfer, policies, farmers’ income level, the development level of agricultural machinery industry, and the cost of using agricultural machinery products have had an important impact on the development of agricultural mechanization. These factors have combined to form a unique mechanism for promoting agricultural mechanization in China [2
]. In addition to factors such as regional economic development, land resources, as well as policy and environment, the AML in a country depends on the improvement of its AEL [7
]. The factors affecting the AEL have also been studied in existing literature [1
]. Liu and Tian [1
] found that the level of economic development is the most important factor affecting the AEL in China, followed by the scale of farmland management and the agricultural planting structure. Yan [23
] also reached similar conclusions.
Although some studies have investigated the factors that influence the AML in China, the effect of the AEL has not been studied in previous literature. Furthermore, the effects of various factors on the AML have not been studied in an integrated analytic framework. A typical single indicator or subjective weighting method is usually adopted to integrate multiple indicators into one indicator. The dependent variable is also set to a single indicator, due to the limitations of the methods used. For example, one can use the total power of agricultural machinery per laborer or use the total power of agricultural machinery to express the AEL [15
], or use the weighted averages of 0.4, 0.3, and 0.3 to indicate the ploughing, seeding, and harvesting mechanization levels, respectively [24
]. Such practices cannot fully reflect the AEL and AML. With these methods, we still need to obtain information on the effect of the AEL on the AML, along with other essential factors that affect the AML, including the economy and technology, social-natural factors, the policy and environmental factors, and the benefit factors. We accomplished this by using structural equation modeling (SEM), which is a systematic analysis method that integrates factor analysis and path analysis. For example, SEM has the advantages of simultaneously processing multiple dependent variables, allowing independent variables and dependent variables to contain measurement errors, estimating factor structures and factor relationships, and estimating the fitting degree of the whole model. In fact, SEM measures not only the relationship between measured variables and latent variables (variables measured by multiple indicators), but also the relationship between two latent variables.
The purpose of this study was to estimate the effect of various factors, including the AEL on the AML in an integrated analytic framework. The results enabled us to understand the influence of the AEL on the AML, to help the policymakers and project implementers of agricultural machinery purchase subsidy policies further design and implement their policies and projects, thus promoting the continuous improvement of agricultural mechanization. The structure of the paper is as follows: Section 2
discusses the conceptual framework, followed by Section 3
, which explains the materials and methods used in this study. Section 4
presents the results and discusses the findings, and the last section concludes the paper.
2. Conceptual Framework
The term AEL refers to the measurement of the holding quantity and technical level of agricultural machinery that applies to agricultural production [20
]. AEL is divided into two indicators: aggregate indicators and average indicators. The aggregate indicators include the total power of agricultural machinery, the original value of agricultural machinery, and the total power of tractors, etc. Of these indicators, the total power of agricultural machinery is the most widely used. The average indicators include the total power of agricultural machinery per laborer or per hectare, as well as the original value of agricultural machinery per labor, and the total power of tractors per hectare. The term AML refers to the level of use of agricultural machinery to provide services for agricultural production. Agricultural mechanization can not only reduce farmers’ labor intensity, but it can also improve agricultural economic efficiency and production efficiency levels, thereby reflecting the technical and management levels of agriculture [25
]. AML relates to the integrated mechanical work level output during the ploughing, seeding, and harvesting of crops. The general method is to weight the proportion of the area of mechanical ploughing, mechanical seeding and mechanical harvesting, respectively, to the total sown area of crops by 0.4, 0.3, and 0.3 [26
]. From the definition and measurement of the two indicators, it can be seen that the AEL is the basis of the AML. Thus, we propose:
The AEL has a positive effect on the AML.
The economic development of a country can promote its AEL and the AML [31
]. The higher the level of economic development, the stronger the investment capacity of agricultural machinery. The higher the opportunity cost of labor, the more frequently the labor-saving technologies will be used (i.e., to achieve mechanized operations through the purchase and employment of agricultural machinery). Thus, the higher the level of economic development in a region, the higher the AEL and AML [20
]. The GDP per capita is an important indicator to reflect the level of regional economic development. The higher the GDP per capita, the lower the proportion of GDP in the primary industry will often be, as the favorable economic development environment and industrial structure have created the optimum conditions for the development of agricultural mechanization [24
]. Farmers account for the main body of agricultural machinery investment, so the per capita net income of farmers is an important factor affecting the AEL and AML [22
], because farmers in higher income areas are more capable of buying more advanced and more applicable agricultural machinery. Thus, based on the above view, we hypothesize:
The level of economic development has a positive impact on both the AEL and AML. Among the indicators of economic development, the GDP per capita and the per capita net income of farmers are positively related to the AEL and AML. The proportion of the primary industry GDP that accounts for the regional GDP is negatively correlated to the AEL and AML.
Land resources provide the basic material conditions of agricultural production. The differences in land resources in terms of quantity, quality, and type determine the differences in agricultural production (production mode, crop type, farming system, etc.). Additionally, the development of agricultural equipment technology in different agricultural production types can have significant differences. Therefore, land resources can indirectly affect the AML through the AEL. The impact of land resources on the AEL is mainly manifested in the following three aspects. First, the scale of land management, the scale effect of agricultural mechanization, and unit operating cost advantages can only be fully manifested on large-scale land areas; the cultivated area per laborer is also usually used to reflect the scale of land management [15
]. Second, with regard to the planting structure (i.e., the main types of crops), the development of the AEL differs, depending on the crop. For example, more and better agricultural equipment is used on wheat crops than that on rice crops. Therefore, the crop planting structure has a significant impact on the AEL [20
]. Third, the natural land conditions play a role in the AEL. For example, it is easier to achieve mechanization in plains and other flat terrains than in hilly and mountainous areas. The development level of machinery technology in plains is also higher than in hilly and mountainous areas. Therefore, the larger the proportion of plains in one region, the higher the AEL. Based on the above view, we hypothesize:
Land resource endowment is positively related to the AEL. That is, the area of agricultural cropping per laborer and the ratio of the area of sown wheat to the total sown area of crops are positively correlated with the AEL, and the ratio of hilly and mountainous area to the total land area is negatively correlated with the AEL.
In agricultural production, agricultural machinery and the agricultural labor force are in an alternative relationship. Therefore, the demographic factor in one region has an impact on that region’s AEL and AML. First, the number of agricultural labor resources is considered. Under the circumstances where the area of cultivated land is certain, where there are fewer agricultural practitioners, and where the farmers are prosperous, the demand for agricultural machinery is greater, and the AML is higher [22
]. Generally, the ratio of primary industry practitioners to society practitioners is used to measure the resource endowment of the agricultural labor force. Second, the transfer situation of agricultural labor force is considered. The process of urbanization in China has led to the transfer of agricultural laborers from rural to urban areas. The essence of agricultural mechanization is the substitution of capital for labor, and the degree of substitution depends on the relative scarcity of capital and labor. The more labor is transferred from agriculture to non-agriculture fields, the scarcer agricultural labor will become. Moreover, the demand for agricultural mechanization will be relatively strong, and then the AML will be improved [15
]. The labor transfer rate is used to represent the transfer of agricultural labor in one region. Third, the knowledge or educational level of agricultural laborers is considered. If farmers have acquired a higher level of education, on the one hand, it is easier for them to grasp the advanced technologies, thus enhancing the AEL. On the other hand, higher education makes it is easier for them to find jobs, thus improving the operating level of agricultural mechanization. Based on the above view, we hypothesize:
Demographic factors have an impact on both the AEL and AML. In other words, the transfer rate of labor and the educational degree of rural residents are in positive correlation to the AEL and AML. The ratio of primary industry practitioners to society practitioners is negatively correlated to the AEL and AML.
Favorable policies and a good environment have a positive effect on the development of agricultural machinery. The subsidy that can be used for purchasing agricultural machinery represents a very important policy in terms of benefiting farmers. Subsidies reduce the cost to farmers of purchasing agricultural machinery, enhance the demand for agricultural machinery, and increase the number of agricultural machines in use [34
]. More importantly, such subsidies improve the AEL. Zhang et al. suggests that the average allowance of the cumulative amount of land per unit area over the years should be used to indicate the impact of purchasing subsidies on the AEL [33
]. Second, the price of agricultural machinery products is considered. According to the supply and demand theory, the prices of agricultural machinery products directly affect the level of farmers’ demand for agricultural machinery. Hou proposes the use of a fixed base price index of mechanized farm machinery to reflect the price of agricultural machinery products [15
]. Third, the level of social services is considered. A good farm machinery socialization service level plays an important positive role in the promotion of the use of advanced agricultural equipment. The number of personnel engaged in agricultural mechanization technology, promotion, education, and training per 10,000 can be regarded as the ratio used to measure the service level [22
]. Based on the above view, we hypothesize:
Policy and environmental factors have an important impact on the AEL. That is, the average subsidy per unit area over the years, and the number of personnel engaged in agricultural mechanization technology, education, promotion, and training per 10,000 members of the labor force is positively related to the AEL. Conversely, agricultural machinery product price and AEL have a negative correlation.
Economic effect reflects whether mechanized operation is reasonable in the economy. It is also one of the prerequisites for the development of agricultural machinery. First of all, with the decline in the number of rural laborers, the saving cost and increasing benefit of agricultural machinery operations and the advantage of land scale have become more obvious [24
]. The pursuit of agricultural production efficiency drives farmers to actively purchase or hire agricultural equipment for mechanized operations, thus improving the AEL and AML. Second, cross-regional operations not only promote the AML, but they also increase farmers’ incomes and achieve good economic and social benefits. As a result, both the AEL and AML can be improved. Mechanized benefit indicators are expressed in terms of agricultural output per laborer and agricultural grain production per laborer. Based on the above view, we hypothesize:
Benefit factors have an impact on both the AEL and AML. That is, agricultural output value per laborer and agricultural grain production per laborer are positively correlated to the AEL and AML.
Based on the hypotheses above, the hypothesis model regarding the factors affecting the AML is shown in Figure 1
Although some studies have investigated the factors affecting the AML in China, the effect of the AEL has not been studied in previous literature. We have modelled the relationship between the AEL and AML using an integrated framework, and therefore, our results confirm the importance of the AEL to the AML. This report can be used to inform the government that the current agricultural machinery purchase subsidy policy must still be strengthened.
In this article, we formulated an integrative framework, using SEM to assess the various factors affecting the AML in China. The results provided solid support for most of our hypotheses. Specifically, the estimated results showed that the AEL had the greatest impact on the AML, and the level of economic development, demographic factors, and benefit factors had not only directly affected the AML but had also indirectly affected the AML through the AEL. In addition, land resource endowment and policy and environmental factors had only an indirect effect on the AML.
Our findings are based on the data available to us. Future research that could enrich our understanding of China’s AML could potentially proceed with longer-term empirical research. Additionally, future research should focus on the AML and AEL in hilly areas and promote the fostering of agricultural machinery service organizations, which mainly provide agricultural mechanization services for small farmers. This could be discussed when adjusting the agricultural machinery purchase subsidy policy in the future. Both the agricultural output value per labor and agricultural grain production per labor have a significant impact on the level of agricultural equipment and the level of agricultural mechanization.